The OSOE program is a real good place to conduct academic research and to collaborate to innovate in the field of Cloud Computing, Information technologies, Business Intelligence, Machine Learning etc.

Research programs

Members of the OSOE program have already performed successful research programs. Those programs involved universities and companies from the open source industry.

Members of the OSOE project are willing to start new researches. The OSOE project is a good place to meet actors of the open source industry and universities involved in open research programs.

"The goal of the project is to provide a formal proof and an experimental proof of the NEO protocol. The NEO protocol is a fully distributed and transactional protocol designed persistent object storage on a Cloud Computing infrastructure."

Academic Publications

Academic publications are also made even outside the framework of a specific research project. Here is a list of publications which have been made in famous place such as IEEE, IFIP and ACM about OSOE technologies.

Book

Students Thesis

Students have successfully benefit of OSOE platform as part of their curriculum. OSOE welcomes students in PhD or in Diploma thesis to use the platform to help the progress of science and pedagogy.

If you are a student and want to benefit from the OSOE project to access the latest technologies and conduct research for your thesis, please contact us. If you already have written your thesis and think we should add a link to it here, please contact us.

List of Thesis

"Disruptive business models, like Software as a Service (SaaS) and free / open source software have made Enterprise Resource Planning (ERP) systems more accessible for Small and Medium Enterprises (SMEs). However, the consulting required to configure an ERP to meet the specific needs of an organization remains a major financial burden for SMEs. Automatic ERP package configuration based on artificial intelligence could be a solution to lessen the burden of the implementation process.

This diplome thesis presents two approaches, based on decision trees and classifiers, to automate selected configuration options of the open source ERP package ERP5. To integrate these approaches into ERP5, the ERP5 Artificial intelligence Toolkit (EAT) has been created. It is a prototype consisting of a set of ERP5 modules which allows to manage and evaluate configuration questions, design decision trees and collect answer data as input for learning classifiers."

"This work develops a tool that aims to replace an existing tool that the excessive use showed serious problems, necessitating the creation of a new tool in addition to correcting the problems, the search for patterns more consolidated and more flexible structure . This work was presented basic concepts that were used to develop this tool and, moreover, along with a description of the tool was presented solutions to known problems. To validate the tool developed, this was applied in a simple case study to use to demonstrate in a real environment."